{"id":"https://openalex.org/W4393036324","doi":"https://doi.org/10.1109/dese60595.2023.10469027","title":"A Study on Data-Driven Energy Forecasting: a Machine Learning Perspective","display_name":"A Study on Data-Driven Energy Forecasting: a Machine Learning Perspective","publication_year":2023,"publication_date":"2023-12-18","ids":{"openalex":"https://openalex.org/W4393036324","doi":"https://doi.org/10.1109/dese60595.2023.10469027"},"language":"en","primary_location":{"id":"doi:10.1109/dese60595.2023.10469027","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/dese60595.2023.10469027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 16th International Conference on Developments in eSystems Engineering (DeSE)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sharath Menon","orcid":null},"institutions":[{"id":"https://openalex.org/I63098007","display_name":"Liverpool John Moores University","ror":"https://ror.org/04zfme737","country_code":"GB","type":"education","lineage":["https://openalex.org/I63098007"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sharath Menon","raw_affiliation_strings":["Liverpool John Moores University United,Liverpool,United Kingdom","Liverpool John Moores University United, Liverpool, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Liverpool John Moores University United,Liverpool,United Kingdom","institution_ids":["https://openalex.org/I63098007"]},{"raw_affiliation_string":"Liverpool John Moores University United, Liverpool, United Kingdom","institution_ids":["https://openalex.org/I63098007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112423996","display_name":"Nailya Sultanova","orcid":null},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Nailya Sultanova","raw_affiliation_strings":["Kazan Federal University,Kazan,Russia","Kazan Federal University, Kazan, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University,Kazan,Russia","institution_ids":["https://openalex.org/I21203515"]},{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033389056","display_name":"Manoj Jayabalan","orcid":"https://orcid.org/0000-0002-1599-965X"},"institutions":[{"id":"https://openalex.org/I63098007","display_name":"Liverpool John Moores University","ror":"https://ror.org/04zfme737","country_code":"GB","type":"education","lineage":["https://openalex.org/I63098007"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Manoj Jayabalan","raw_affiliation_strings":["Liverpool John Moores University,Liverpool,United Kingdom","Liverpool John Moores University, Liverpool, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Liverpool John Moores University,Liverpool,United Kingdom","institution_ids":["https://openalex.org/I63098007"]},{"raw_affiliation_string":"Liverpool John Moores University, Liverpool, United Kingdom","institution_ids":["https://openalex.org/I63098007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035982173","display_name":"Jamila Mustafina","orcid":"https://orcid.org/0000-0001-5770-4111"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Jamila Mustafina","raw_affiliation_strings":["Kazan Federal University,Kazan,Russia","Kazan Federal University, Kazan, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University,Kazan,Russia","institution_ids":["https://openalex.org/I21203515"]},{"raw_affiliation_string":"Kazan Federal University, Kazan, Russia","institution_ids":["https://openalex.org/I21203515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"702","last_page":"705"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.7588465213775635},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6218546628952026},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5033301711082458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41796523332595825},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41487962007522583},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38293954730033875},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06280729174613953}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7588465213775635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6218546628952026},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5033301711082458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41796523332595825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41487962007522583},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38293954730033875},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06280729174613953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dese60595.2023.10469027","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/dese60595.2023.10469027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 16th International Conference on Developments in eSystems Engineering (DeSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2765626411","https://openalex.org/W2995219715","https://openalex.org/W3021030633","https://openalex.org/W3028586177","https://openalex.org/W3087860540","https://openalex.org/W3116240832","https://openalex.org/W3200006629","https://openalex.org/W4200052800","https://openalex.org/W4200215659","https://openalex.org/W4210955934","https://openalex.org/W4220842087","https://openalex.org/W4282560500"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"However,":[0],"energy":[1,17,30,33,61,68,108,125,133],"forecasting":[2,69],"is":[3,51],"still":[4],"a":[5,54,114],"challenging":[6],"task":[7],"due":[8],"to":[9,52],"the":[10,75,89,119],"many":[11,76],"unpredictable":[12],"factors":[13],"that":[14,82],"can":[15,83,112,128],"impact":[16],"consumption":[18],"and":[19,29,39,64,80,95,105,136],"production,":[20],"such":[21,100],"as":[22,41,101],"changes":[23],"in":[24,107,124],"weather":[25],"patterns,":[26],"economic":[27],"conditions,":[28],"policies.":[31],"Therefore,":[32],"forecasts":[34],"should":[35],"be":[36,71,84],"continuously":[37],"updated":[38],"refined":[40],"new":[42],"information":[43],"becomes":[44],"available.":[45],"The":[46,86],"purpose":[47],"of":[48,66,91,118,121],"this":[49],"research":[50,111],"present":[53],"high-level,":[55],"machine":[56,77],"learning-centric":[57],"viewpoint":[58],"on":[59],"data-driven":[60,67],"forecasting.":[62,109],"Challenges":[63],"constraints":[65],"will":[70],"discussed,":[72],"along":[73],"with":[74],"learning":[78,94],"methods":[79],"methodologies":[81],"implemented.":[85],"paper":[87],"compares":[88],"performance":[90],"various":[92],"deep":[93],"time":[96],"series":[97],"analysis":[98],"techniques":[99],"LSTM,":[102],"RNN,":[103],"ARIMA":[104],"SARIMA":[106],"This":[110],"provide":[113],"more":[115],"comprehensive":[116],"understanding":[117],"effectiveness":[120],"different":[122],"models":[123],"forecasting,":[126],"which":[127],"have":[129],"significant":[130],"implications":[131],"for":[132],"management,":[134],"policymaking,":[135],"infrastructure":[137],"development.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
